The CRAM Cognitive Architecture for Robot Manipulation in Everyday Activities

Understand

This paper presents a hybrid robot cognitive architecture, CRAM, that enables robot agents to accomplish everyday manipulation tasks.

• It addresses five key challenges that arise when carrying out everyday activities.
• These include (i) the underdetermined nature of task specification, (ii) the generation of context-specific behavior, (iii) the ability to make decisions based on knowledge, experience, and prediction, (iv) the ability to reason at the levels of motions and sensor data, and (v) the ability to explain actions and the consequences of these actions.
• We explore the computational foundations of the CRAM cognitive model: the self-programmability entailed by physical symbol systems, the CRAM plan language, generalized action plans and implicit-to-explicit manipulation, generative models, digital twin knowledge representation & reasoning, and narrative-enabled episodic memories.